Search for exploits based on file hash analysis using neural networks

Abstract

Search for exploits based on file hash analysis using neural networks

Erokhin V.V., Aksenov A.V.

Incoming article date: 07.06.2025

The purpose of the article: to determine the possibility of using file hash analysis using artificial neural networks to detect exploits in files. Research method: the search for exploits in files is carried out based on the analysis of Windows registry file hashes obtained by two hashing algorithms SHA-256 and SHA-512, using three types of artificial neural networks (direct propagation, recurrent, convolutional). The obtained result: the use of artificial neural networks in file hash analysis allows us to identify exploits or malicious records in files; the performance (accuracy) of artificial neural networks of direct propagation and with recurrent architecture are comparable to each other and are much more productive than convolutional neural networks; the longer the length of the file hash, the more reliably it is to identify an exploit in the file.

Keywords: malware, exploit, neural networks, hashing, modeling